DBMS > DolphinDB vs. mSQL vs. openGemini vs. Splice Machine

System Properties Comparison DolphinDB vs. mSQL vs. openGemini vs. Splice Machine

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

mSQL (Mini SQL) is a simple and lightweight RDBMS

An open source distributed Time Series DBMS with high concurrency, high performance, and high scalability

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Secondary database models

Relational DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Score	0.09
Rank	#361	Overall
	#37	Time Series DBMS

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Website

www.dolphindb.com

hughestech.com.au/products/msql

www.opengemini.org
github.com/openGemini

splicemachine.com

Technical documentation

docs.dolphindb.cn/en/help200/index.html

docs.opengemini.org/guide

splicemachine.com/how-it-works

Developer

DolphinDB, Inc

Hughes Technologies

Huawei and openGemini community

Splice Machine

Initial release

2018

1994

2022

2014

Current release

v2.00.4, January 2022

4.4, October 2021

1.1, July 2023

3.1, March 2021

License

Commercial or Open Source

commercial

free community version available

commercial

free licenses can be provided

Open Source

Apache Version 2.0

Open Source

AGPL 3.0, commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Java

Server operating systems

Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
Windows

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Integer, Float, Boolean, String

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

SQL-like query language

yes

APIs and other access methods

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

JDBC
ODBC

HTTP REST

JDBC
Native Spark Datasource
ODBC

Supported programming languages

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

C
C++
Delphi
Java
Perl
PHP
Tcl

C
C++
Go
Java
JavaScript (Node.js)
Python
Rust

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Sharding

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Administrators, Users, Groups

Administrators and common users accounts

Access rights for users, groups and roles according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Higher Education PS rules out ghost students before PAC
29 November 2018, diggers.news

provided by Google News

About HUAWEI Open Source
9 February 2022, Huawei

provided by Google News

Machine learning data pipeline outfit Splice Machine files for insolvency
26 August 2021, The Register

Splice Machine Launches the Splice Machine Feature Store to Simplify Feature Engineering and Democratize Machine ...
19 January 2021, PR Newswire

Distributed SQL System Review: Snowflake vs Splice Machine
18 September 2019, Towards Data Science

Splice Machine Launches Feature Store to Simplify Feature Engineering
19 January 2021, Datanami

Splice Machine scores $15M to make Hadoop run in real time
10 February 2014, VentureBeat

provided by Google News

Share this page